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- Publisher Website: 10.1016/j.cor.2013.09.013
- Scopus: eid_2-s2.0-84885340283
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Article: A holonic approach to flexible flow shop scheduling under stochastic processing times
Title | A holonic approach to flexible flow shop scheduling under stochastic processing times |
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Authors | |
Keywords | Back propagation network Contract net protocol Decomposition Flexible flow shop Holonic manufacturing system Neighbouring K-means clustering algorithm Stochastic processing times |
Issue Date | 2014 |
Publisher | Elsevier. |
Citation | Computers and Operations Research, 2014, v. 43, p. 157–168 How to Cite? |
Abstract | Flexible flow shop scheduling problems are NP-hard and tend to become more complex when stochastic uncertainties are taken into consideration. This paper presents a novel decomposition-based holonic approach (DBHA) for minimising the makespan of a flexible flow shop (FFS) with stochastic processing times. The proposed DBHA employs autonomous and cooperative holons to construct solutions. When jobs are released to an FFS, the machines of the FFS are firstly grouped by a neighbouring K-means clustering algorithm into an appropriate number of cluster holons, based on their stochastic nature. A scheduling policy, determined by the back propagation networks (BPNs), is then assigned to each cluster holon for schedule generation. For cluster holons of a low stochastic nature, the Genetic Algorithm Control (GAC) is adopted to generate local schedules in a centralised manner; on the other hand, for cluster holons of a high stochastic nature, the Shortest Processing Time Based Contract Net Protocol (SPT-CNP) is applied to conduct negotiations for scheduling in a decentralised manner. The combination of these two scheduling policies enables the DBHA to achieve globally good solutions, with considerable adaptability in dynamic environments. Computation results indicate that the DBHA outperforms either GAC or SPT-CNP alone for FFS scheduling with stochastic processing times. |
Persistent Identifier | http://hdl.handle.net/10722/198488 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | WANG, K | en_US |
dc.contributor.author | Choi, SH | en_US |
dc.date.accessioned | 2014-07-07T07:12:49Z | - |
dc.date.available | 2014-07-07T07:12:49Z | - |
dc.date.issued | 2014 | en_US |
dc.identifier.citation | Computers and Operations Research, 2014, v. 43, p. 157–168 | en_US |
dc.identifier.uri | http://hdl.handle.net/10722/198488 | - |
dc.description.abstract | Flexible flow shop scheduling problems are NP-hard and tend to become more complex when stochastic uncertainties are taken into consideration. This paper presents a novel decomposition-based holonic approach (DBHA) for minimising the makespan of a flexible flow shop (FFS) with stochastic processing times. The proposed DBHA employs autonomous and cooperative holons to construct solutions. When jobs are released to an FFS, the machines of the FFS are firstly grouped by a neighbouring K-means clustering algorithm into an appropriate number of cluster holons, based on their stochastic nature. A scheduling policy, determined by the back propagation networks (BPNs), is then assigned to each cluster holon for schedule generation. For cluster holons of a low stochastic nature, the Genetic Algorithm Control (GAC) is adopted to generate local schedules in a centralised manner; on the other hand, for cluster holons of a high stochastic nature, the Shortest Processing Time Based Contract Net Protocol (SPT-CNP) is applied to conduct negotiations for scheduling in a decentralised manner. The combination of these two scheduling policies enables the DBHA to achieve globally good solutions, with considerable adaptability in dynamic environments. Computation results indicate that the DBHA outperforms either GAC or SPT-CNP alone for FFS scheduling with stochastic processing times. | en_US |
dc.language | eng | en_US |
dc.publisher | Elsevier. | en_US |
dc.relation.ispartof | Computers and Operations Research | en_US |
dc.rights | NOTICE: this is the author’s version of a work that was accepted for publication in <Journal title>. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in PUBLICATION, [VOL#, ISSUE#, (DATE)] DOI# | en_US |
dc.subject | Back propagation network | - |
dc.subject | Contract net protocol | - |
dc.subject | Decomposition | - |
dc.subject | Flexible flow shop | - |
dc.subject | Holonic manufacturing system | - |
dc.subject | Neighbouring K-means clustering algorithm | - |
dc.subject | Stochastic processing times | - |
dc.title | A holonic approach to flexible flow shop scheduling under stochastic processing times | en_US |
dc.type | Article | en_US |
dc.identifier.email | Choi, SH: shchoi@hkucc.hku.hk | en_US |
dc.identifier.authority | Choi, SH=rp00109 | en_US |
dc.identifier.doi | 10.1016/j.cor.2013.09.013 | en_US |
dc.identifier.scopus | eid_2-s2.0-84885340283 | - |
dc.identifier.hkuros | 229955 | en_US |
dc.identifier.volume | 43 | en_US |
dc.identifier.spage | 157–168 | en_US |
dc.identifier.epage | 157–168 | en_US |
dc.identifier.isi | WOS:000329383300015 | - |